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Workforce Management in Periodic Delivery Operations

Author

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  • Karen Smilowitz

    (Industrial Engineering and Management Sciences, McCormick School of Engineering, Northwestern University, Evanston, Illinois, 60208)

  • Maciek Nowak

    (Information Systems and Operations Management, Graduate School of Business, Loyola University, Chicago, Illinois, 60611)

  • Tingting Jiang

    (Industrial Engineering and Management Sciences, McCormick School of Engineering, Northwestern University, Evanston, Illinois, 60208)

Abstract

Service quality and driver efficiency in the delivery industry may be enhanced by increasing the regularity with which a driver visits the same set of customers. However, effectively managing a workforce of drivers may increase travel distance, a traditional metric of the vehicle routing problem (VRP). This paper evaluates the effect that workforce management has on routing costs, providing insight for managerial decision making. The analysis is presented in the context of the period vehicle routing problem (PVRP), an extension of the VRP with vehicle routes constructed to service customers according to preset visit frequencies over an established period of time. We develop models to apply workforce management principles. Through a computational study with standard PVRP test cases and real-world delivery data, we show that multiobjective PVRP models can achieve a balance between workforce management and travel distance goals. With the proper parameters in place, workforce management principles may be successfully applied without sacrificing other operational objectives.

Suggested Citation

  • Karen Smilowitz & Maciek Nowak & Tingting Jiang, 2013. "Workforce Management in Periodic Delivery Operations," Transportation Science, INFORMS, vol. 47(2), pages 214-230, May.
    • Handle: RePEc:inm:ortrsc:v:47:y:2013:i:2:p:214-230
    DOI: 10.1287/trsc.1120.0407
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    References listed on IDEAS

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    Cited by:

    1. Chen, Lu & Chen, Yuyi & Langevin, André, 2021. "An inverse optimization approach for a capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1087-1098.
    2. Li, Yifu & Zhou, Chenhao & Yuan, Peixue & Ngo, Thi Tu Anh, 2023. "Experience-based territory planning and driver assignment with predicted demand and driver present condition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    3. Mike Hewitt & Maciek Nowak & Nisha Nataraj, 2016. "Planning Strategies for Home Health Care Delivery," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(05), pages 1-26, October.
    4. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    5. Michael Schneider & Andreas Stenger & Fabian Schwahn & Daniele Vigo, 2015. "Territory-Based Vehicle Routing in the Presence of Time-Window Constraints," Transportation Science, INFORMS, vol. 49(4), pages 732-751, November.
    6. Liu, Chuanju & Lin, Shaochong & Shen, Zuo-Jun Max & Zhang, Junlong, 2023. "Stochastic service network design: The value of fixed routes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
    7. Ulmer, Marlin & Nowak, Maciek & Mattfeld, Dirk & Kaminski, Bogumił, 2020. "Binary driver-customer familiarity in service routing," European Journal of Operational Research, Elsevier, vol. 286(2), pages 477-493.
    8. Rodríguez-Martín, Inmaculada & Yaman, Hande, 2022. "Periodic Vehicle Routing Problem with Driver Consistency and service time optimization," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 468-484.
    9. Anirudh Subramanyam & Chrysanthos E. Gounaris, 2018. "A Decomposition Algorithm for the Consistent Traveling Salesman Problem with Vehicle Idling," Transportation Science, INFORMS, vol. 52(2), pages 386-401, March.
    10. Hongyan Dai & Peng Liu, 2020. "Workforce planning for O2O delivery systems with crowdsourced drivers," Annals of Operations Research, Springer, vol. 291(1), pages 219-245, August.
    11. Mohsen Emadikhiav & David Bergman & Robert Day, 2020. "Consistent Routing and Scheduling with Simultaneous Pickups and Deliveries," Production and Operations Management, Production and Operations Management Society, vol. 29(8), pages 1937-1955, August.
    12. Zhou, Lin & Zhen, Lu & Baldacci, Roberto & Boschetti, Marco & Dai, Ying & Lim, Andrew, 2021. "A Heuristic Algorithm for solving a large-scale real-world territory design problem," Omega, Elsevier, vol. 103(C).
    13. Jost, Christian & Jungwirth, Alexander & Kolisch, Rainer & Schiffels, Sebastian, 2022. "Consistent vehicle routing with pickup decisions - Insights from sport academy training transfers," European Journal of Operational Research, Elsevier, vol. 298(1), pages 337-350.
    14. Hewitt, Mike & Nowak, Maciek & Gala, Leo, 2015. "Consolidating home meal delivery with limited operational disruption," European Journal of Operational Research, Elsevier, vol. 243(1), pages 281-291.
    15. Attila A. Kovacs & Bruce L. Golden & Richard F. Hartl & Sophie N. Parragh, 2015. "The Generalized Consistent Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 796-816, November.
    16. Bender, Matthias & Kalcsics, Jörg & Meyer, Anne, 2020. "Districting for parcel delivery services – A two-Stage solution approach and a real-World case study," Omega, Elsevier, vol. 96(C).
    17. Zhen, Lu & Gao, Jiajing & Tan, Zheyi & Laporte, Gilbert & Baldacci, Roberto, 2023. "Territorial design for customers with demand frequency," European Journal of Operational Research, Elsevier, vol. 309(1), pages 82-101.
    18. Leandro C. Coelho & Jean-François Cordeau & Gilbert Laporte, 2014. "Thirty Years of Inventory Routing," Transportation Science, INFORMS, vol. 48(1), pages 1-19, February.

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